L'ensemble de données sous-jacent de ce produit EVI (Enhanced Vegetation Index) est constitué d'images MODIS corrigées par BRDF (MCD43B4), qui ont été complétées à l'aide de l'approche décrite dans Weiss et al. (2014) pour éliminer les données manquantes causées par des facteurs tels que la couverture nuageuse. Les sorties sans lacunes ont ensuite été agrégées temporellement et spatialement pour produire le produit mensuel d'environ 5 km.
Cet ensemble de données a été produit par Harry Gibson et Daniel Weiss du Malaria Atlas Project (Big Data Institute, Université d'Oxford, Royaume-Uni, https://malariaatlas.org/).
Bracelets
Taille des pixels 5 000 mètres
Bandes de fréquences
Nom
Unités
Min
Max
Taille des pixels
Description
Mean
0*
1*
mètres
Valeur moyenne de l'indice de végétation amélioré pour chaque pixel agrégé.
FilledProportion
%
0*
100*
mètres
Bande de contrôle qualité qui indique le pourcentage de chaque pixel résultant composé de données brutes (par opposition aux estimations avec données manquantes).
Weiss, D.J., P.M. Atkinson, S. Bhatt, B. Mappin, S.I. Hay & P.W. Gething
(2014) An effective approach for gap-filling continental scale remotely
sensed time-series. ISPRS Journal of Photogrammetry and Remote Sensing,
98, 106-118.
L'ensemble de données sous-jacent de ce produit Enhanced Vegetation Index (EVI) est constitué d'images MODIS corrigées par BRDF (MCD43B4), qui ont été complétées à l'aide de l'approche décrite dans Weiss et al. (2014) pour éliminer les données manquantes causées par des facteurs tels que la couverture nuageuse. Les sorties sans lacunes ont ensuite été agrégées de manière temporelle et spatiale pour produire les …
[null,null,[],[[["\u003cp\u003eThis dataset provides monthly Enhanced Vegetation Index (EVI) data from 2001-02-01 to 2015-06-01, derived from MODIS imagery and gap-filled for cloud cover.\u003c/p\u003e\n"],["\u003cp\u003eIt is produced by the Oxford Malaria Atlas Project and available at a 5km resolution.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset includes a 'Mean' band representing EVI values and a 'FilledProportion' band indicating the percentage of raw data used in each pixel.\u003c/p\u003e\n"],["\u003cp\u003eData is licensed under CC-BY-NC-SA-4.0, requiring attribution, non-commercial use, and share-alike distribution.\u003c/p\u003e\n"],["\u003cp\u003eUsers can explore and analyze this dataset within Google Earth Engine.\u003c/p\u003e\n"]]],[],null,["# Oxford MAP EVI: Malaria Atlas Project Gap-Filled Enhanced Vegetation Index\n\nDataset Availability\n: 2001-02-01T00:00:00Z--2015-06-01T00:00:00Z\n\nDataset Provider\n:\n\n\n [Oxford Malaria Atlas Project](https://www.bdi.ox.ac.uk/research/malaria-atlas-project)\n\nCadence\n: 1 Month\n\nTags\n:\n[evi](/earth-engine/datasets/tags/evi) [map](/earth-engine/datasets/tags/map) [oxford](/earth-engine/datasets/tags/oxford) [vegetation](/earth-engine/datasets/tags/vegetation) [vegetation-indices](/earth-engine/datasets/tags/vegetation-indices) \n\n#### Description\n\nThe underlying dataset for this Enhanced Vegetation Index (EVI)\nproduct is MODIS BRDF-corrected imagery (MCD43B4), which was gap-filled\nusing the approach outlined in Weiss et al. (2014) to eliminate missing\ndata caused by factors such as cloud cover. Gap-free outputs were then\naggregated temporally and spatially to produce the monthly ≈5km product.\n\nThis dataset was produced by Harry Gibson and Daniel Weiss of the\nMalaria Atlas Project (Big Data Institute, University of Oxford,\nUnited Kingdom, \u003chttps://malariaatlas.org/\u003e).\n\n### Bands\n\n\n**Pixel Size**\n\n5000 meters\n\n**Bands**\n\n| Name | Units | Min | Max | Pixel Size | Description |\n|--------------------|-------|-----|-------|------------|---------------------------------------------------------------------------------------------------------------------------------------------------|\n| `Mean` | | 0\\* | 1\\* | meters | The mean value of the Enhanced Vegetation Index for each aggregated pixel. |\n| `FilledProportion` | % | 0\\* | 100\\* | meters | A quality control band that indicates the percentage of each resulting pixel that was comprised of raw data (as opposed to gap-filled estimates). |\n\n\\* estimated min or max value\n\n### Terms of Use\n\n**Terms of Use**\n\n[CC-BY-NC-SA-4.0](https://spdx.org/licenses/CC-BY-NC-SA-4.0.html)\n\n### Citations\n\nCitations:\n\n- Weiss, D.J., P.M. Atkinson, S. Bhatt, B. Mappin, S.I. Hay \\& P.W. Gething\n (2014) An effective approach for gap-filling continental scale remotely\n sensed time-series. ISPRS Journal of Photogrammetry and Remote Sensing,\n 98, 106-118.\n\n### Explore with Earth Engine\n\n| **Important:** Earth Engine is a platform for petabyte-scale scientific analysis and visualization of geospatial datasets, both for public benefit and for business and government users. Earth Engine is free to use for research, education, and nonprofit use. To get started, please [register for Earth Engine access.](https://console.cloud.google.com/earth-engine)\n\n### Code Editor (JavaScript)\n\n```javascript\nvar dataset = ee.ImageCollection('Oxford/MAP/EVI_5km_Monthly')\n .filter(ee.Filter.date('2015-01-01', '2015-12-31'));\nvar evi = dataset.select('Mean');\nvar eviVis = {\n min: 0.0,\n max: 1.0,\n palette: [\n 'ffffff', 'fcd163', '99b718', '66a000', '3e8601', '207401', '056201',\n '004c00', '011301'\n ],\n};\nMap.setCenter(-60.5, -20.0, 2);\nMap.addLayer(evi, eviVis, 'EVI');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/Oxford/Oxford_MAP_EVI_5km_Monthly) \n[Oxford MAP EVI: Malaria Atlas Project Gap-Filled Enhanced Vegetation Index](/earth-engine/datasets/catalog/Oxford_MAP_EVI_5km_Monthly) \nThe underlying dataset for this Enhanced Vegetation Index (EVI) product is MODIS BRDF-corrected imagery (MCD43B4), which was gap-filled using the approach outlined in Weiss et al. (2014) to eliminate missing data caused by factors such as cloud cover. Gap-free outputs were then aggregated temporally and spatially to produce the monthly ... \nOxford/MAP/EVI_5km_Monthly, evi,map,oxford,vegetation,vegetation-indices \n2001-02-01T00:00:00Z/2015-06-01T00:00:00Z \n-90 -180 90 180 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [](https://doi.org/https://www.bdi.ox.ac.uk/research/malaria-atlas-project)\n- [](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/Oxford_MAP_EVI_5km_Monthly)"]]
